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A Modified Radiopropagation Multipath Model for Constant Refractivity Gradient Profiles

Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2023年第2期22卷 298-312页

作者： Parada, D. Rego, C.G. Guevara, D. Navarro, A. Ramos, G.L. Oliveira, R. Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Antônio Carlos 6627 MG Belo Horizonte Brazil Departament of Electronics Engineering Universidade Federal de Minas Gerais MG Belo HorizonteCEP 31270-901 Brazil Departament of Electricity and Electronics Universidad Francisco de Paula Santander Norte de Santander CúcutaCEP 540003 Colombia Departament of Information and Communication Technologies Universidad ICESI Cali Valle del CaucaCEP 760031 Colombia Departament of Telecommunications and Mechatronics Engineering Federal University of São João del-Rei MG Ouro BrancoCEP 36415-000 Brazil

This paper presents a radiopropagation algorithm based on a Ray Tracing (RT) technique that combines a modified multipath model for constant refractivity gradient profiles and the Uniform Theory of Diffraction (UTD). A novel formulation is proposed by the authors for calculation and ground-reflection analysis of ray paths depending on atmospheric refractivity. The algorithm introduced herein was evaluated in a mixed scenario and in two more realistic case studies, under conditions of constant refractivity gradient and lossy terrain profiles. Pathloss results are obtained and compared with Parabolic Equation (PE) numerical solution results at 2.0 GHz, 3.5 GHz and 5.4 GHz. In such conditions, the modified radiopropagation multipath algorithm with atmospheric refractivity introduced herein showed satisfactory results. © 2023 SBMO/SBMag.

关键词： Refraction

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A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks

A Novel Hybrid Framework for Energy-Efficient Clustering and...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Gopal Kumar Gupta Arpit Jain Khemraj Sharma P. M. Ashok Kumar Shubhi Gupta Sheenu Agarwal Symbiosis Institute Of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Business Administration Doctoral Program in Management Sciences NANHUA UNIVERSITY Dalin Chiayi R.O.C Department of Computer Science and Engineering Amity University Greater Noida Uttar Pradesh India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Smart computing has been particularly notable in the development of wireless sensor networks (WSNs), which have many applications. Battery-powered, self-configuring sensor nodes are the basis of these networks. Energy and resources are limited when it comes to sensors. Unbalanced nodes in the network consume more power, which adversely affects the network’s lifespan. An improved energy-efficient cluster-based routing protocol for heterogeneous wireless sensor networks (WSNs) based on the Internet of Things is proposed in this study. Several performance metrics were used to evaluate the proposed model’s effectiveness, including energy efficiency, alive nodes, dead nodes, network lifetime, and residual energy. The results of the comparison were compared with existing methodologies, such as LEACH, PSO, and hybrid PSO. The proposed approach outperforms the existing model by a substantial margin in networks with 50 and 100 nodes, according to the simulation results.

关键词： Wireless communication Measurement Wireless sensor networks Simulation Heuristic algorithms Routing Energy efficiency Routing protocols Internet of Things Informatics

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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Enhancing Blockchain Scalability: Innovative Solutions for Optimized Performance in Decentralized Networks

Enhancing Blockchain Scalability: Innovative Solutions for O...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Akanksha Srivastav Sheenu Agarwal Arpit Jain Shikha Tayal Shalu Jain Khemraj Sharma Tula’s institute Dehradun U.K. India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India Department of Computer Science & Engineering Koneru Lakshamaiah Education Foundation Vadessahwaram A.P. India Department of Computer Science & Engineering Tula’s Institute Dehradun Uttarakhand India Maharaja Agrasen Himalayan Garhwal University Pauri Garhwal Uttarakhand Department: Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi R.O.C

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

A substantial number of people are presently making use of decentralised cryptocurrencies that are built on blockchain technology. These crypto currencies have garnered a lot of interest over the course of the last few years and are currently being used by their users. Being the first use of blockchain technology, Bitcoin has been a resounding success, which drives further research and improvement in the sector concerned with blockchain technology. Bitcoin was the first usage of blockchain technology. Bitcoin, on the other hand, is susceptible to significant performance issues due to the fact that it has a high transaction latency and a limited throughput. The operations of the cryptocurrency are considerably impacted as a result of these concerns. As a result of the fact that other cryptocurrencies that rely on proof-of-work also carry over its deficiencies, there has been an increase in the number of concerns about the scalability of blockchain technology. The fact that this is the case makes scaling blockchain technology more challenging. All during the course of this investigation, an effort is made to analyse and classify the various scaling mechanisms that are now being used for blockchains. In addition to this, we are going to look at a variety of various approaches and present a list of possible solutions to the issue of scalability that the blockchain technology is now dealing.

关键词： Hands Computers Distributed ledger Scalability Bitcoin Throughput Proof of Work Fabrics Blockchains Informatics

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GaAs nanowhiskers for femtosecond photodetectors and THz emitters

GaAs nanowhiskers for femtosecond photodetectors and THz emi...

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International Conference on Advanced Semiconductor Devices and Microsystems (ASDAM)

作者： M. Mikulics J. Zhang R. Sobolewski R. Adam L. Juul M. Marso A. Winden H. Hardtdegen D. Grützmacher P. Kordoš Peter Grünberg Institut (PGI) Forschungszentrum Jülich (KFA) Julich Germany Department of Electrical and Computer Engineering and Laboratory for Laser Energetics University of Rochester Rochester NY USA Department of Electrical and Computer Engineering and Laboratory for Laser Energetics Department of Physics and Astronomy and Materials Science Program University of Rochester Rochester NY USA Faculté des Sciences de la Technologie et de la Communication Université du Luxembourg Luxembourg Institute of Electrical Engineering Institute of Electronics and Photonics Slovak Academy of Sciences Bratislava Slovakia

We have developed and characterized ultrafast and highly sensitive photodetectors based on GaAs nanowhiskers fabricated with an improved top-down etching method. We evaluated the material properties of the etched nanowhiskers by micro photoluminescence measurements and studied the effect of post annealing on nanowhiskers' luminescence. The nanowhiskers were integrated into the coplanar striplines for device testing using DC and time-resolved electro-optic characterization techniques. Our photodetectors exhibit a very low dark current below 500 pA at 10 V bias as well as a high responsivity of 0.19 A/W at 30 V, and a cut-off frequency of 1.3 THz. These characteristics make the GaAs nanowhisker photodetectors very promising candidates for high-speed optoelectronics and efficient THz emitters.

关键词： Gallium arsenide Photodetectors Annealing Etching Semiconductor device measurement Fabrication Nanoscale devices

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Correction: Microstructuring of cobalt (Co) thin films by UV laser irradiation

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Applied Physics A 2023年第1期130卷 1-1页

作者： Itapu, Srikanth Borra, Vamsi Selvendran, S. Department of Electronics and Communication Engineering Alliance University Bengaluru India Electrical and Computer Engineering Program Rayen College of Engineering Youngstown State University Youngstown USA Centre for Healthcare Advancement Innovation and Research (CHAIR) School of Electronics Engineering (SENSE) Vellore Institute of Technology Chennai India

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Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Van Huynh, Nguyen Du, Hongyang Hoang, Dinh Thai Niyato, Dusit Zhu, Kun Kang, Jiawen Xiong, Zehui Jamalipour, Abbas In Kim, Dong The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney Australia The School of Computer Science and Engineering Nanyang Technological University Singapore College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Information Engineering University of Sydney Australia The College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions. © 2024, CC BY.

关键词： Metadata

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Fabrication of SiN films at low temperature by RF biased coaxial-line microwave plasma CVD

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electronics AND communicationS IN JAPAN PART II-electronics 1996年第11期79卷 58-65页

作者： Morita, Y Kato, I Nakajima, T School of Science and Engineering Waseda University Tokyo Japan Received a B.S. in 1992 from the Department of Electronics and Communication Waseda University. He is now enrolled in the Ph.D. program at the same university. He has been involved in research on microwave plasma CVD. He is a member of the Japanese Society of Applied Physics. Received the B.S. and Ph.D. degrees from the Department of Electronics and Communication Waseda University in 1967 and 1973 respectively. In 1973 he joined the faculty of Waseda University becoming an associate professor in 1978. He was Visiting Professor at Manitoba University Canada in 1979–1981. He has supervised research and participated in joint research with die Canadian National Research Council. He became a professor at Waseda University in 1993. He has been involved in research on microwave plasma CVD photonics lasers electronic materials evaluation technologies photonic materials opto-quantum electronics and semiconductor dun films. He is a member of die IEE of Japan die Japan Society of Applied Physics die TV Society die Japanese Vacuum Society and IEEE. Received die B.S. from die Department of Electronics and Communication Waseda University in 1994. He is now enrolled in die master's program at die same university. He has been involved in research on microwave plasma CVD. He is a member of die Japan Society of Applied Physics.

This paper discusses the influence of ion bombardment on the characteristics of SiN films. In this study, the double-tube coaxial-line microwave plasma CVD system, which is suitable for the investigation of ion bombardment, is used to deposit SiN films. The ion bombardment energy is varied by varying the RF bias at constant ion density, As the RF bias is increased, the film density increases and the hydrogen concentration decreases, but the dangling bond density increases. The increase in the film density and decrease of hydrogen concentration are caused by the increase in film surface temperature, while the increase of the dangling bond density is caused by bond breakage due to the N+ ion implantation. When the substrate temperature is 200 degrees C and the RF bias is -175 V, the film density is 3 g/cm(3) and the hydrogen concentration is 9 at.% because of the film surface heating effect of ion bombardment acid also due to substrate heating. Substrate heating at 200 degrees C suppresses the increase in the dangling bond density. It is also demonstrated that the film surface temperature is about 200 degrees C when RF bias is -70 similar to-80 V and the substrate is unheated by any heater.

关键词： microwave plasma CVD SiN film RF bias ion bombardment effect film surface hearing effect

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Fault detection and analysis in nuclear research facility using artificial intelligence methods

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AIP Conference Proceedings 2016年第1期1704卷

作者： Abu Bakar Ghazali Maslina Mohd Ibrahim 1Department of Electronics & Communication College of Engineering Universiti Tenaga Nasional 43009 Kajang Selangor Malaysia 2Instrumentation Program Malaysian Nuclear Agency Bangi Malaysia

In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.

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Smart photonic wristband for pulse wave monitoring

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Opto-Electronic Science 2024年第12期3卷 12-27页

作者： Renfei Kuang Zhuo Wang Lin Ma Heng Wang Qingming Chen Arnaldo Leal Junior Santosh Kumar Xiaoli Li Carlos Marques Rui Min Center for Cognition and Neuroergonomics State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityZhuhai 519087China College of Science Shenyang Aerospace UniversityShenyang 110136China School of Microelectronics Science and Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and SystemsSun Yat-Sen UniversityZhuhai 519082China Graduate Program in Electrical Engineering Federal University of Espírito SantoFernando Ferrari AvenueVitoria 29075-910Brazil Department of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh 522302India CICECO-Aveiro Institute of Materials Physics DepartmentUniversity of AveiroAveiro 3810-193Portugal

Real-time acquisition of human pulse signals in daily life is clinically important for cardiovascular disease monitoring and ***,we propose a smart photonic wristband for pulse signal monitoring based on speckle pattern analysis with a polymer optical fiber(POF)integrated into a sports *** different speckle pattern processing algorithms and POFs with different core diameters were *** results indicated that the smart photonic wristband had a high signal-to-noise ratio and low latency,with the measurement error controlled at approximately 3.7%.This optimized pulse signal could be used for further medical diagnosis and was capable of objectively monitoring subtle pulse signal changes,such as the pulse waveform at different positions of Cunkou and pulse waveforms before and after *** the assistance of artificial intelligence(AI),functions such as gesture recognition have been realized through the established prediction model by processing pulse signals,in which the recognition accuracy reaches 95%.Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring,paving the way for medical Internet of Things-enabled smart systems.

关键词： smart healthcare specklegram pulse monitoring gesture recognition artificial intelligence wearable sensor

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